{"id":"W2297607658","doi":"","title":"Drought Preparedness and Response as if Development Matters: Case Studies from Kenya","year":2011,"lang":"en","type":"article","venue":"Journal of rural and community development","topic":"Disaster Management and Resilience","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Vulnerability (computing); Disaster risk reduction; Emergency management; Preparedness; Community resilience; Environmental planning; Government (linguistics); Psychological intervention; Resilience (materials science); Environmental resource management; Vulnerability assessment; Economic growth; Political science; Geography; Resource (disambiguation); Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001994977,0.0001311959,0.0002290285,0.00009982935,0.001463204,0.00009694363,0.0002928972,0.00004233432,0.00006027262],"category_scores_gemma":[0.0001186788,0.00009829656,0.00002635907,0.0001080029,0.0003235136,0.0003833175,0.0003720934,0.0002519889,0.000007897441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001373785,"about_ca_system_score_gemma":0.0002619643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009206191,"about_ca_topic_score_gemma":0.001407359,"domain_scores_codex":[0.9982522,0.0007788094,0.0003946612,0.00006635165,0.0003057226,0.0002022555],"domain_scores_gemma":[0.9990745,0.0002860839,0.0002280286,0.0001118813,0.0001437501,0.0001557534],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003829327,0.0001480921,0.003033065,0.00002300191,0.0001961066,0.0003271355,0.9368203,1.844901e-7,0.00002866907,0.00009222684,0.0005825443,0.05836579],"study_design_scores_gemma":[0.0004563148,0.0001236776,0.04840358,0.0002722137,0.00003484493,0.0002241224,0.9169202,4.475152e-7,0.0002182718,0.001201927,0.03193504,0.0002093056],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970087,0.0006644149,0.00002377617,0.0005627663,0.0002170753,0.0001008698,6.081931e-7,0.00001270951,0.001409043],"genre_scores_gemma":[0.9947115,0.0004603635,0.003196666,0.0003148929,0.0000276178,0.000004401278,6.756848e-7,0.000005022559,0.001278841],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05815648,"threshold_uncertainty_score":0.9998367,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05849537456147766,"score_gpt":0.3160866471470439,"score_spread":0.2575912725855662,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}